Digital Marketing Strategy: AI, Analytics and Innovation

A profound and transformational learning experience for you. Immediate and actionable insights for your organisation.

Key topics

How you learn

Digital Marketing Strategy: AI, Analytics and Innovation seamlessly integrates strategy and big-picture thinking with hands-on simulations and practical exposure to the most innovative and transformational technologies reshaping digital marketing today. You will actively explore new tools and approaches, then rigorously evaluate outputs against evidence-based frameworks. Through live simulations and exercises -including building digital ads, coordinating campaigns, running optimization experiments, developing AI-assisted predictive models, creating digital synthetic data, and other analytical challenges - you'll learn to distinguish AI-generated content that feels right from content that performs right. Common sense and intuition often mislead us about what drives attention, memory, and action; you'll learn when to trust data over instinct, and when human judgment remains irreplaceable. You'll analyse results with peers who face similar strategic challenges, and with faculty who combine cutting-edge academic research with real-world consultancy experience. The programme is led by LSE experts working at the bleeding edge of innovation in digital marketing, and convenes participants from diverse industries, sectors and organisations to expedite and broaden your learning and understanding.

View the provisional programme timetable below:

Hands-On Simulations and Live Experimentation

This programme is built around active learning, not passive lectures. You will:

Use AI/LLMs for your specific marketing context, evaluating outputs against evidence-based frameworks for content stickiness, engagement, and conversion effectiveness.

Learn how different content structures, schema markup, and conversational query optimisation affect AI-driven search results in real-time across platforms like ChatGPT, Claude, and Google AI Overviews.

Develop predictive models using synthetic data to forecast campaign performance, customer churn, and lifetime value before committing budget to market testing.

Create and refine synthetic data and digital twins of customer segments to test messaging strategies, channel preferences, and offer combinations without market risk or the delays of traditional research.

Conduct Google Ad campaign design challenges, balancing strategic goals beyond immediate ROI - brand building, customer acquisition cost, lifetime value optimisation - through live platform simulations. Each simulation connects tactical execution to strategic outcomes, helping you understand not just how to use these tools but when and why they create competitive advantage in your specific context.

Digital Marketing Strategy: AI, Analytics and Innovation is designed for executives from both marketing and non-marketing roles and from a diversity of industries, profit and not-for-profit.

Participants include:

• Current or aspiring marketing directors and decision-makers
• Executives from non-marketing functions looking to understand data and evidence-based strategic marketing practices
• Entrepreneurs and executives working in start-ups
• Website managers
• Not-for-profit executives

Strategic Applications Across Sectors

The frameworks and AI tools covered in this programme have immediate relevance across diverse contexts. Recent participants and organisations applying similar approaches include:

Government & Policy: Saudi Arabia's Public Investment Fund (PIF) and the UK's Competition & Markets Authority (CMA) use AI-powered market intelligence and predictive analytics to inform strategic investment decisions and regulatory priorities.

International Development: UNHCR deploys conversational AI and sentiment analysis to improve refugee service delivery, predict migration patterns, and allocate resources more effectively across regions.

Consumer Brands: Companies like Procter & Gamble use digital twins to simulate consumer response to new product concepts, packaging changes, and messaging strategies before committing manufacturing resources—dramatically reducing the cost and risk of innovation.

Healthcare & Pharmaceuticals: Organizations leverage generative engine optimization to ensure evidence-based health information appears prominently in AI-driven search results, countering misinformation and supporting informed patient decisions.

Financial Services: Banks use predictive analytics to anticipate customer churn and personalise retention campaigns at the individual level, while using conversational AI to handle routine inquiries and free relationship managers for complex advisory conversations.

Retail & E-commerce: Brands optimise for voice search and answer engines as consumers increasingly bypass traditional search results, fundamentally changing how product discovery happens online.

Whether you're marketing to consumers, businesses, governments, or donors - and whether your objectives are revenue growth, policy influence, or social impact - the strategic principles remain constant even as tactical execution varies by context.

At LSE, we unfailingly deliver the integrated strategic and tactical understanding that you need to see the connections, join the dots and take decisive action. Our world-class suite of executive programmes draws on the interdisciplinary expertise of our faculty to ensure you see the big picture and the minutiae within the challenges you face. Each learning experience is calibrated to give you competition-beating strategies and hands-on skills and tools, from forecasting and predictive analytics to data aggregation, modelling and personalisation. You emerge with the holistic view, the insights and the specific capabilities to design and deliver next-generation digital marketing strategies - and sustain your competitive advantage in a crowded and volatile market. Crucially, our approach combines technical mastery with critical evaluation. You won't just learn which AI tools exist - you'll learn how to assess whether they deliver genuine strategic value for your specific context, how to avoid common pitfalls including over-reliance on intuition when evidence provides better guidance, and when human judgment and creativity remain irreplaceable despite AI's capabilities.

This programme is taught by:

Entry requirements

All LSE executive education participants are required to have:

• Fluency in English, proficiency level or working knowledge of the language is essential
• A good undergraduate degree or significant work experience in a relevant role(s).
• Minimum five years’ professional experience. Typically our participants have more than ten years’ work experience, but we will consider those with less experience who have enjoyed an accelerated career path to a senior level.

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